Update app.py

app.py

@@ -2,21 +2,25 @@ import streamlit as st
 import os
 import json
 import requests
-import google.generativeai as genai
+from google import genai
+from google.genai import types
+from dotenv import load_dotenv
 
-# Load environment variables
-api_key = os.getenv("GOOGLE_API_KEY")
-finance_key = os.getenv("FINANCE_KEY")
+load_dotenv()
 
-if not api_key or not finance_key:
-    st.error("API keys not found. Please check your configuration.")
-    st.stop()
+# Set page configuration
+st.set_page_config(
+    page_title="Flaix - Financial Assistant",
+    page_icon="💰",
+    layout="centered"
+)
 
 # Initialize Gemini client
-genai.configure(api_key=api_key)
+api_key = st.secrets["GOOGLE_API_KEY"]
+client = genai.Client(api_key=api_key)
 
 # Indian Stock Market API base configuration
-INDIAN_API_KEY = finance_key
+INDIAN_API_KEY = st.secrets["FINANCE_KEY"]
 INDIAN_API_BASE_URL = "https://stock.indianapi.in"
 
 # Define API endpoints and their parameters
@@ -27,7 +31,50 @@ API_ENDPOINTS = {
         "param_mapping": {"stock_name": "name"},
         "description": "Get details for a specific stock"
     },
-    # ... (rest of your code)
+    "get_trending_stocks": {
+        "endpoint": "/trending",
+        "required_params": [],
+        "param_mapping": {},
+        "description": "Get trending stocks in the market"
+    },
+    "get_market_news": {
+        "endpoint": "/news",
+        "required_params": [],
+        "param_mapping": {},
+        "description": "Get latest stock market news"
+    },
+    "get_mutual_funds": {
+        "endpoint": "/mutual_funds",
+        "required_params": [],
+        "param_mapping": {},
+        "description": "Get mutual funds data"
+    },
+    "get_ipo_data": {
+        "endpoint": "/ipo",
+        "required_params": [],
+        "param_mapping": {},
+        "description": "Get IPO data"
+    },
+    "get_bse_most_active": {
+        "endpoint": "/BSE_most_active",
+        "required_params": [],
+        "param_mapping": {},
+        "description": "Get BSE most active stocks"
+    },
+    "get_nse_most_active": {
+        "endpoint": "/NSE_most_active",
+        "required_params": [],
+        "param_mapping": {},
+        "description": "Get NSE most active stocks"
+    },
+    "get_historical_data": {
+        "endpoint": "/historical_data",
+        "required_params": ["stock_name"],
+        "optional_params": ["period"],
+        "default_values": {"period": "1m", "filter": "default"},
+        "param_mapping": {},
+        "description": "Get historical data for a stock"
+    }
 }
 
 # Unified API call function
@@ -86,6 +133,7 @@ def call_api_by_name(api_name, **kwargs):
             mapped_params[param] = value
     
     return call_indian_api(endpoint, mapped_params)
+
 # Improved orchestrator function
 def orchestrator(query):
     """
@@ -95,21 +143,17 @@ def orchestrator(query):
     # Create a more precise prompt for the orchestrator
     orchestrator_prompt = """
     You are an orchestrator for a financial assistant specialized in Indian markets. Your job is to analyze user queries and determine if they need real-time market data.
-
     IMPORTANT: Be very precise in your analysis. Only return TRUE for "needs_api" when the query EXPLICITLY asks for current market data, stock prices, or listings.
-
     Examples where needs_api should be TRUE:
     - "Show me the most active stocks on NSE today" → get_nse_most_active
     - "What is the current price of Reliance?" → get_stock_details with stock_name="Reliance"
     - "Tell me about trending stocks" → get_trending_stocks
     - "What are the latest IPOs?" → get_ipo_data
-
     Examples where needs_api should be FALSE:
     - "What is compound interest?"
     - "How should I start investing?"
     - "What are the tax benefits of PPF?"
     - "Explain mutual funds to me"
-
     Available API functions:
     - get_stock_details(stock_name): Get details for a specific stock
     - get_trending_stocks(): Get trending stocks in the market
@@ -119,9 +163,7 @@ def orchestrator(query):
     - get_bse_most_active(): Get BSE most active stocks
     - get_nse_most_active(): Get NSE most active stocks
     - get_historical_data(stock_name, period="1m"): Get historical data for a stock
-
     User query: """ + query + """
-
     Respond in JSON format with the following structure:
     {
         "needs_api": true/false,
@@ -135,16 +177,28 @@ def orchestrator(query):
         
     # Create content for the orchestrator
     contents = [
-        {
-            "role": "user",
-            "parts": [orchestrator_prompt]
-        }
+        types.Content(
+            role="user",
+            parts=[
+                types.Part.from_text(text=orchestrator_prompt)
+            ],
+        ),
     ]
     
+    # Configure generation parameters
+    generate_content_config = types.GenerateContentConfig(
+        temperature=0.2,
+        top_p=0.95,
+        top_k=40,
+        max_output_tokens=500,
+        response_mime_type="text/plain",
+    )
+    
     # Generate content
-    response = genai.generate_content(
+    response = client.models.generate_content(
         model="gemini-1.5-flash",
         contents=contents,
+        config=generate_content_config,
     )
     
     # Parse the response
@@ -163,11 +217,11 @@ def orchestrator(query):
     except Exception as e:
         print(f"Error parsing orchestrator response: {e}")
         return {"needs_api": False}
+
 # Language setting
 
 # Financial assistant system prompt
 SYSTEM_PROMPT = f"""You are Flaix, a helpful and knowledgeable financial assistant designed specifically for Indian users. Your purpose is to improve financial literacy and provide guidance on investments in the Indian market.
-
 Key responsibilities:
 1. Explain financial concepts in simple, easy-to-understand language
 2. Provide information about different investment options available in India (stocks, mutual funds, bonds, PPF, FDs, etc.)
@@ -299,4 +353,4 @@ if prompt := st.chat_input("Ask me anything about finance or investing..."):
             message_placeholder.write(full_response)
         
         # Add assistant response to chat history
-        st.session_state.messages.append({"role": "model", "content": full_response})
+        st.session_state.messages.append({"role": "model", "content": full_response})